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Hybrid Routing: Towards Resilient Routing in Anonymous Communication Networks

Hybrid Routing: Towards Resilient Routing in Anonymous Commu...

引用

IEEE International Conference on Communications (ICC)

作者： Yusheng Xia Rongmao Chen Jinshu Su Chen Pan Han Su College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Anonymous communication networks (ACNs) are intended to protect the metadata during communication. As classic ACNs, onion mix-nets are famous for strong anonymity, in which the source defines a static path and wraps the message multi-times with the public keys of nodes on the path, through which the message is relayed to the destination. However, onion mix-nets lacks in resilience when the static on-path mixes fail. Mix failure easily results in message loss, communication failure, and even specific attacks. Therefore, it is desirable to achieve resilient routing in onion mix-nets, providing persistent routing capability even though node failure. The state-of-theart solutions mainly adopt mix groups and thus need to share secret keys among all the group members which may cause single point of failure. To address this problem, in this work we propose a hybrid routing approach, which embeds the onion mix-net with hop-by-hop routing to increase routing resilience. Furthermore, we propose the threshold hybrid routing to achieve better key management and avoid single point of failure. As for experimental evaluations, we conduct quantitative analysis of the resilience and realize a local T-hybrid routing prototype to test performance. The experimental results show that our proposed routing strategy increases routing resilience effectively, at the expense of acceptable latency.

关键词： Routing Resilience Public key Peer-to-peer computing Encryption

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An Online/Offline HIBS Scheme for Privacy Protection of People-centric Sensing

An Online/Offline HIBS Scheme for Privacy Protection of Peop...

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International Conference on Industrial Informatics, computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII)

作者： Peixin Chen Xiaofeng Wang Jinshu Su College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467383134

People-Centric Sensing (PCS), which collects information closely related to human activity and interactions in societies, is stepping into a flourishing time. Along with its great benefits, PCS poses new security challenges such as data integrity, participant privacy. Hierarchical Identity-Based Signature (HIBS) scheme can efficiently provide high integrity messaging, secure communication and privacy protection to PCS. However, the low computation efficiency primarily hinders the PCS adoption of HIBS scheme. In this paper, we propose an online/offline HIBS (HIBOOS) scheme for securing PCS. By splitting the signing phase into online and offline procedures, our scheme achieves high signing efficiency.

关键词： Games Sensors Privacy Public key Generators Wireless sensor networks

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FedHybrid: Hierarchical Hybrid Training for High-Performance Federated Learning

FedHybrid: Hierarchical Hybrid Training for High-Performance...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Tao Chang Li Li Meihan Wu Wei Yu Xiaodong Wang National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China State Key Laboratory of Internet of Things for Smart City University of Macau China The 30th Research Institute of China Electronics Technology Group Corporation China

Federated Learning coordinates multiple devices to train a shared model while preserving data privacy. Despite its potential benefit, the increasing number of participating devices poses new challenges to the deployment in real-world cases. The highly limited amount of data located on each device coupled with significantly unbalanced data across different devices severely impede the performance of the shared model and the overall training progress at the same *** this paper, we propose FedHybrid, a hierarchical hybrid training framework for high-performance Federated Learning on a wide scale. Unlike the existing work that mainly focuses on the statistical challenge, FedHybrid establishes a hierarchical hybrid training framework that effectively utilizes the fragmented and unbalanced data located on the participating devices on a wide scale. Specifically, FedHybrid consists of the following two core components, a global coordinator deployed on the central server and a local coordinator deployed on each participating device. The global coordinator organizes the participating devices into different groups through jointly considering the system heterogeneity and unbalanced training data in order to accelerate the overall training progress while guaranteeing the model performance. Within each group, a novel device-to-device (D2D) sequential training procedure is coordinated by the local coordinator to effectively utilize the fragmented and unbalanced training data in order to intelligently update the local models. At the same time, we provide the theoretical analysis of FedHybrid and conduct extensive experiments to evaluate its effectiveness. The results show that FedHybrid effectively improves model accuracy up to 27% and accelerates the whole training process by 20% on average.

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A Hierarchical Memory Service Mechanism in Server Consolidation Environment

A Hierarchical Memory Service Mechanism in Server Consolidat...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Liufeng Wang Huaimin Wang Lu Cai Rui Chu Pengfei Zhang Lanzheng Liu National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China School of Economics and Management Xi'an University Xi'an China

Increasing Internet business and computing footprint motivate server consolidation in data centers. Through virtualization technology, server consolidation can reduce physical hosts and provide scalable services. However, the ineffective memory usage among multiple virtual machines (VMs) becomes the bottleneck in server consolidation environment. Because of inaccurate memory usage estimate and the lack of memory resource managements, there is much service performance degradation in data centers, even though they have occupied a large amount of memory. In order to improve this scenario, we first introduce VM's memory division view and VM's free memory division view. Based on them, we propose a hierarchal memory service mechanism. We have designed and implemented the corresponding memory scheduling algorithm to enhance memory efficiency and achieve service level agreement. The benchmark test results show that our implementation can save 30% physical memory with 1% to 5% performance degradation. Based on Xen virtualization platform and balloon driver technology, our works actually bring dramatic benefits to commercial cloud computing center which is providing more than 2,000 VMs' services to cloud computing users.

关键词： Memory management Resource management Servers Scheduling algorithm Benchmark testing Cloud computing System performance

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HPGA: A High-Performance Graph Analytics Framework on the GPU

HPGA: A High-Performance Graph Analytics Framework on the GP...

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International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Haoduo Yang Huayou Su Mei Wen Chunyuan Zhang Department of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781538657393;9781538657386

In recent years, the rapidly growing use of graphs has sparked parallel graph analytics frameworks for leveraging the massive hardware resources, specifically graphics processing units (GPUs). However, the issues of the unpredictable control flows, memory divergence, and the complexity of programming have restricted high-level GPU graph libraries. In this work, we present HPGA, a high performance parallel graph analytics framework targeting the GPU. HPGA implements an abstraction which maps vertex programs to generalized sparse matrix operations on GPUs for delivering high performance. HPGA incorporates high-performance GPU computing primitives and optimization strategies with a high-level programming model. We evaluate the performance of HPGA for three graph primitives (BFS, SSSP, PageRank) with large-scale datasets. The experimental results show that HPGA matches or even exceeds the performance of MapGraph and nvGRAPH, two state-of-the-art GPU graph libraries.

关键词： Graphics processing units Sparse matrices Programming Computational modeling Arrays Optimization

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Tendency-based caching in Content-Centric Networking

Tendency-based caching in Content-Centric Networking

引用

International Conference on Ubiquitous and Future Networks, ICUFN

作者： YuSheng Xia YaPing Liu JinShu Su College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467399920

In content-centric networking, the schemes of innetwork caching can affect the performance of the whole network. Existing schemes lack of the global view, which results in inefficient caches. In this paper, we aim to analyze the real-time distribution of contents among caches from multiple perspectives. This paper proposes TCBRP, a scheme that analyzes caching tendency of various contents in reverse path, based on centrality of nodes, popularity of contents and replacement rate of nodes, to cache in-network contents. This scheme also has decent scalability and can be expended conveniently. The experimental results reflect that TCBRP report savings in average hops and balance cache hit rate, compared with BetwRep and LCE.

关键词： Probability Internet Network architecture Mathematical model Statistical analysis Correlation Fading channels

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Simulation of Nuclear Reactor Accident Scenarios using Physics-Informed Neural Networks and Transfer-Learning 4

Simulation of Nuclear Reactor Accident Scenarios using Physi...

引用

4th International Conference on Electronic Information Engineering and Computer Science, EIECS 2024

作者： Yu, Yang Xie, Yufei Wang, Wenlin Wu, Guohua Lan, Haitao Lin, Enbo An, Ping Sun, Zibin Zhang, Haichuan Wu, Yixian National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China Nuclear Power Institute of China Science and Technology on Reactor System Design Technology Laboratory Chengdu China School of Automation Wuhan University of Technology Wuhan China Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Institute of Automotive Engineers Hubei University of Automotive Technology Shiyan China Nuclear Power Institute of China Chengdu China

ISBN: (纸本)9798331531409

In a Loss of Coolant Accident (LOCA), reactor core temperatures can rise rapidly, leading to potential fuel damage and radioactive material release. This research presents a groundbreaking method that combines the power of Monte Carlo Sampling and Physics-Informed Neural Networks (PINNs) to simulate and effectively address the challenging Loss of Coolant Accidents (LOCA) in nuclear reactors. In the event of a LOCA, reactor core temperatures can soar rapidly, posing a significant threat to fuel integrity and potentially leading to the release of radioactive materials. By leveraging the strengths of both Monte Carlo Sampling and PINNs, this approach aims to provide a comprehensive and accurate simulation framework for assessing and mitigating the consequences of such accidents. The method yields high prediction accuracy (MAE: 0.033, RMSE: 0.098, R2: 0.814) and demonstrates robustness through transfer learning, maintaining strong performance (MAE: 0.064, RMSE: 0.163, R2: 0.735). © 2024 IEEE.

关键词： Coolants

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Large-scale Network Topology Generation for Emulation Environment

Large-scale Network Topology Generation for Emulation Enviro...

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The First International Conference on Networking and distributed computing(第一届网络与分布式计算国际会议 ICNDC 2010)

作者： Xu Fei Li Jin Kuang Xiao-hui Huang Min-huan Che Yong-gang National Key Laboratory of Science and Technology on Information System Security Beijing Institute National Key Laboratory of Science and Technology on Information System Security Beijing Institute National Laboratory for Parallel and Distributed Process National University of Defense Technology

Network emulation environment is great importance to the research of network protocols, applications and security mechanism. Large-scale network topology generation b one of key technologies to construct network emulation environment. In this paper, a new large-scale network topology generation framework called LSNTGF is proposed, which divides the network topology into three hierarchies: AS, router and terminal node. It contains the assignment mechanism to bandwidth of each link and IP address of each node. The framework is evaluate by implementation, and the result illustrate it is efficient to network emulation environment for network protocols and security research.

关键词： Large-scale network topology generation bandwidth assignment IP address assignment

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Mitigating sync amplification for copy-on-write virtual disk 16

Mitigating sync amplification for copy-on-write virtual disk

引用

Proceedings of the 14th Usenix Conference on File and Storage Technologies

作者： Qingshu Chen Liang Liang Yubin Xia Haibo Chen Hyunsoo Kim Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Samsung Electronics Co. Ltd.

ISBN: (纸本)9781931971287

Copy-on-write virtual disks (e.g., qcow2 images) provide many useful features like snapshot, de-duplication, and full-disk encryption. However, our study uncovers that they introduce additional metadata for block organization and notably more disk sync operations (e.g., more than 3X for qcow2 and 4X for VMDK images). To mitigate such sync amplification, we propose three optimizations, namely per virtual disk internal journaling, dual-mode journaling, and adaptive-preallocation, which eliminate the extra sync operations while preserving those features in a consistent way. Our evaluation shows that the three optimizations result in up to 110% performance speedup for varmail and 50% for TPCC.

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Grid and Cooperative computing - GCC 2004 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302087

ISBN: (纸本)9783540235644

Welcome to the proceedings of GCC2004 and the city of Wuhan. Grid computing has become a mainstream research area in computer science and the GCC conference has become one of the premier forums for presentation of new and exciting research in all aspectsofgridandcooperativecomputing. Theprogramcommitteeispleasedtopresent the proceedings of the 3rd International Conference on Grid and Cooperative Comp- ing (GCC2004), which comprises a collection of excellent technical papers, posters, workshops, and keynote speeches. The papers accepted cover a wide range of exciting topics, including resource grid and service grid, information grid and knowledge grid, grid monitoring,managementand organizationtools, grid portal, grid service, Web s- vices and their QoS, service orchestration, grid middleware and toolkits, software glue technologies, grid security, innovative grid applications, advanced resource reservation andscheduling,performanceevaluationandmodeling,computer-supportedcooperative work, P2P computing, automatic computing, and meta-information management. The conference continues to grow and this year a record total of 581 manuscripts (including workshop submissions) were submitted for consideration. Expecting this growth, the size of the program committee was increased from 50 members for GCC 2003 for 70 in GCC 2004. Relevant differences from previous editions of the conf- ence: it is worth mentioning a signi?cant increase in the number of papers submitted by authors from outside China; and the acceptance rate was much lower than for p- vious GCC conferences. From the 427 papers submitted to the main conference, the program committee selected only 96 regular papers for oral presentation and 62 short papers for poster presentation in the program.

关键词： Theory of Computation Computer Communication Networks Operating Systems Software Engineering Information Systems Applications (incl. Internet) Information Storage and Retrieval

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